





'''simple docstring'''

from statistics import mean

import numpy as np





def 		UpperCamelCase							(				_lowerCamelCase   :   Tuple		,			_lowerCamelCase   :   Dict		,			_lowerCamelCase   :   List[Any]		,			_lowerCamelCase   :   int			):
    A__							=     0
    # Number of processes finished
    A__							=     0
    # Displays the finished process.
    # If it is 0, the performance is completed if it is 1, before the performance.
    A__							=     [0] * no_of_process
    # List to include calculation results
    A__							=     [0] * no_of_process

    # Sort by arrival time.
    A__							=     [burst_time[i] for i in np.argsort(_lowerCamelCase			)]
    A__							=     [process_name[i] for i in np.argsort(_lowerCamelCase			)]
    arrival_time.sort()

    while no_of_process > finished_process_count:
        A__							=     0
        while finished_process[i] == 1:
            i += 1
        if current_time < arrival_time[i]:
            A__							=     arrival_time[i]

        A__							=     0
        # Index showing the location of the process being performed
        A__							=     0
        # Saves the current response ratio.
        A__							=     0
        for i in range(0		,			_lowerCamelCase			):
            if finished_process[i] == 0 and arrival_time[i] <= current_time:
                A__							=     (burst_time[i] + (current_time - arrival_time[i])) / burst_time[
                    i
                ]
            if response_ratio < temp:
                A__							=     temp
                A__							=     i

        # Calculate the turn around time
        A__							=     current_time + burst_time[loc] - arrival_time[loc]
        current_time += burst_time[loc]
        # Indicates that the process has been performed.
        A__							=     1
        # Increase finished_process_count by 1
        finished_process_count += 1

    return turn_around_time





def 		UpperCamelCase							(				_lowerCamelCase   :   str		,			_lowerCamelCase   :   List[str]		,			_lowerCamelCase   :   Optional[Any]		,			_lowerCamelCase   :   Optional[int]			):
    A__							=     [0] * no_of_process
    for i in range(0		,			_lowerCamelCase			):
        A__							=     turn_around_time[i] - burst_time[i]
    return waiting_time


if __name__ == "__main__":
  __lowerCAmelCase				:      Optional[Any]						      =5
  __lowerCAmelCase				:      List[str]						      =["""A""", """B""", """C""", """D""", """E"""]
  __lowerCAmelCase				:      List[Any]						      =[1, 2, 3, 4, 5]
  __lowerCAmelCase				:      Tuple						      =[1, 2, 3, 4, 5]

  __lowerCAmelCase				:      Tuple						      =calculate_turn_around_time(
      process_name, arrival_time, burst_time, no_of_process
  )
  __lowerCAmelCase				:      str						      =calculate_waiting_time(
      process_name, turn_around_time, burst_time, no_of_process
  )

  print("Process name \tArrival time \tBurst time \tTurn around time \tWaiting time")
  for i in range(0, no_of_process):
    print(
        f"""{process_name[i]}\t\t{arrival_time[i]}\t\t{burst_time[i]}\t\t"""
        f"""{turn_around_time[i]}\t\t\t{waiting_time[i]}"""
    )

  print(f"""average waiting time : {mean(waiting_time):.5f}""")
  print(f"""average turn around time : {mean(turn_around_time):.5f}""")




"""simple docstring"""



from __future__ import annotations

import math



def 	_lowerCamelCase(	a   ,    a				):
       __a       =    u
       for i in range(1   ,    a				):
              __a       =    temp * (u - i)
       return temp



def 	_lowerCamelCase(	):
       __a       =    int(input("enter the numbers of values: "				)				)
       __a       =    []
       for _ in range(a				):
              y.append([]				)
       for i in range(a				):
              for j in range(a				):
                     y[i].append(a				)
                     __a       =    0

       print("enter the values of parameters in a list: "				)
       __a       =    list(map(a   ,    input().split()				)				)

       print("enter the values of corresponding parameters: "				)
       for i in range(a				):
              __a       =    float(input()				)

       __a       =    int(input("enter the value to interpolate: "				)				)
       __a       =    (value - x[0]) / (x[1] - x[0])

       # for calculating forward difference table

       for i in range(1   ,    a				):
              for j in range(n - i				):
                     __a       =    y[j + 1][i - 1] - y[j][i - 1]

       __a       =    y[0][0]
       for i in range(1   ,    a				):
              summ += (ucal(a   ,    a				) * y[0][i]) / math.factorial(a				)

       print(F"the value at {value} is {summ}"				)


if __name__ == "__main__":
   main()
